Claim Record

Claim records exist as physical paper files in adjuster cabinets or as unstructured email threads and phone notes. No consistent template or required fields exist across adjusters. Loss details, claimant contact information, and coverage decisions are captured informally at adjuster discretion.

None — AI cannot parse inconsistent handwritten notes or unstructured emails to extract claim details, determine coverage, or predict reserves. Every claim requires manual adjuster review from first notice through settlement.

Claims are entered into a digital system using standardized intake forms with required fields for FNOL, but the structure is minimal. Adjusters type free-text narratives into large text boxes. Coverage determination, reserve amounts, and payment history exist as separate records but lack consistent identifiers linking them together as a unified claim lifecycle.

Keyword search and basic reporting are possible. AI can extract claimant names and policy numbers from structured fields, but cannot interpret free-text narratives to assess liability, detect fraud indicators, or predict appropriate reserve amounts without adjuster guidance.

Claim records capture the full lifecycle with structured fields for FNOL details, coverage determination rationale, reserve history with timestamps, payment records linked to invoices, and claim status. Liability assessment, subrogation potential, and settlement authority are documented in discrete fields. Each claim includes claimant contact details, policy coverage, and adjuster assignment.

AI can perform FNOL triage by analyzing loss cause and severity, recommend initial reserves based on historical similar claims, and flag claims for SIU review based on fraud indicators. However, AI cannot fully automate complex liability determinations or settlement negotiations without adjuster oversight.

Claims records include comprehensive structured detail: injury descriptions by body part with severity codes, comparative negligence percentages, repair line-item estimates with part numbers and labor codes, settlement negotiation history with date-stamped offers, and explicit rationale fields for coverage decisions and reserve adjustments. Medical treatment timelines and provider details are captured in linked records.

AI can automate routine coverage decisions for clear-cut claims, recommend reserve adjustments based on injury progression patterns, and suggest settlement ranges incorporating comparative negligence. For complex multi-party liability or disputed coverage claims, AI provides decision support but requires adjuster final approval.

Claims records incorporate standardized industry taxonomies: ISO loss cause codes, ICD-10 medical codes for injuries, Mitchell repair procedure codes, and jurisdiction-specific legal citation formats. Each claim links to external references including comparable case law outcomes, NCCI medical treatment guidelines, local labor rate databases, and historical settlement data for similar claims in the same jurisdiction.

AI can automate end-to-end handling of routine claims including coverage determination, reserve setting, fraud screening, settlement calculation, and payment authorization for straightforward cases. Complex claims with disputed liability, policy ambiguity, or litigation potential still require adjuster intervention.

Claim records are fully formalized with explicit decision logic: coverage interpretation rules reference specific policy language and case precedent, subrogation evaluation follows scored criteria (recovery probability, legal cost estimates), and settlement authority thresholds are defined by algorithmic risk scoring. Every adjudication decision is traceable to formal rules, enabling AI to replicate expert judgment and explain its reasoning by citing the specific rules applied.

Fully autonomous claims adjudication for routine and moderately complex claims, including coverage decisions, reserve optimization, fraud investigation initiation, and settlement execution. AI handles 80%+ of claims without adjuster involvement, escalating only outlier scenarios or claims exceeding authority thresholds.

Ceiling of the CMC framework for this dimension.